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How Web Bots Freed $2M
from a Billing Bottleneck
Session 79, February 12, 2019
Mary Wickersham, Vice President of Central Business Office
Ryan Ayres, Senior Vice President of Strategic Solutions
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Mary Wickersham
Ryan Ayres
Has no real or apparent conflicts of interest to report.
Conflict of Interest
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Introductions
Learning objectives
Business Office challenges
Workflow design
Solution evaluation & design
Outcomes and financial results
What’s next for Avera Health with RPA?
Q&A
Agenda
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Learning Objective 1: Appraise the use of automation for
communicating with payers about billing and insurance matters
Learning Objective 2: Explain how robotic process automation
queries, retrieves and normalizes data from payer websites
Learning Objective 3: Describe how robotic process automation
routes billing and insurance data to defined workflows and
designated staff
Learning Objectives
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Business Office Challenges
& Organizational Improvement Goals
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Rapid system growth creating increased claims backlog
Significant delays in achieving timely follow-up on unpaid accounts
Limited automation opportunities in patient accounting system
Staff dissatisfaction and turnover
Business Office challenges
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Reduce volume of unpaid accounts needing payment status
review
Accelerate cash by reviewing accounts pre-remit
Avoid hiring additional staff
Avoid checking status on pending/paid accounts
Reduce aged Accounts Receivable (AR)
Reduce days in Accounts Receivable (AR)
Reduce timely filing write-offs
Organizational goals
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Workflow design
Achieving automation with intelligent content
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Existing insurance claim
status workflow
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EDI claim status is limited
Status
Category
Status
Code
F2 -
Denied
0 No Further
Status Available
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Web-sourced data via RPA
adds more depth
Payer
EDI Status
ReconBot
Result
Payer A
Non
-covered
charge(s)
Remark Code SF: This claim is being denied
because our records indicate
patient has a
primary medical insurance with another
company
.
Payer B
Plan procedures not
followed
Remark Code 1005: Benefits were reduced due to
failure to obtain pre
-certification approval as
outlined in the plan.
Payer C
Claim/service lacks
information
Remark Code E5904:
until we receive specific
requested medical information.
Payer D
Processed according
to contract provisions
Remark Code 08Z: Denied because these services
were not emergent,
nor have we received a
referral.
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Authorization as an example
Code
Description
1210
Claim processed based on the level of care authorized.
1273
Services are reduced or denied for no behavioral health authorization on file.
The provider is prohibited from billing the patient for this amount. If you have
already paid this amount, please request a refund.
1274
Our records do not reflect an authorization on file and additional information
from the health care professional is needed to review the claim for medical
necessity. Please submit facility records..
AK
Claim processed as authorized.
HT
Authorization required, yet no prior authorization was obtained for these
services.
XV8
Pre
-
treatment authorization required, but not obtained. Please submit medical
necessity.
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Best practice for intelligent
workflow
RETRIEVE NORMALIZE CLASSIFY INTEGRATE
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Normalization and classification
of web-sourced data
EDI Existing Workflow
Status Category: F2
Denied
Status Code: 107
Proc According to
Contract
Denials Queue
Status Category: F0
Finalized No Action
Status Code: 107
Proc According to
Contract
Research Queue
Web-sourced Data New Workflow
Payer-Specific Code:
W1 Amount applied to
deductible. Allowed
Amt = Deductible Amt
Paid, Not Posted
Payer-Specific
Code: 34B
This service
is not allowed because
diagnosis code(s) are
inappropriately coded.
Clinical Coding
BEFORE AFTER
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Commercial B: Partial Payment
Paid: $<Number> Payment Date: <Date> CHK #:<Number>
Code: 149 Doesn’t meet Medicare NCD/LCD criteria.
Context-specific notation drives
workflow
Claim Status
Deferred
PAID
Deferred
- PENDING
Prioritized
-Specific Reason Codes,
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Outcomes and financial
results
RPA Is making almost 80% of claims “touchless”
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Daily patient accounting system integration tasks:
Detailed note content
Activate or defer account based on status
Remediation queue designation
Intelligent workflow
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Expected outcomes
Automate
status on
inventory of
all accounts
Avoid
website
research
and logging
Stop working
paid or
pending
claims
Focus solely
on claims
needing
remediation
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Cost effective resource
utilization
Claim Remediation Experts (High Cost)Claim Remediation Experts (High Cost)
• Medical
Necessity Denials
•• Authorization
Denials
•• Complex
Denials
Patient Access (Mid Cost)Patient Access (Mid Cost)
Coverage Issues
• Policy Changes
• Benefit
Coordination
Clerks (Low Cost)Clerks (Low Cost)
• Information
Requests
• Patient
Engagement
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Actual outcomes
Outcome
Metric
Increased efficiency in handling problem
claims because no longer working non
-
response claims, such as ‘paid’ or ‘pending’
Avoided hiring additional
5
-7 FTEs
Significant impacts to account aging
-
Payer 1 A/R> 90 dropped from 10% to 6%
-
Payer 2 A/R> 90 dropped from 20% to 7%
Accounts addressed in 57
days or less, trending to
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Acceleration of outstanding receivables
$20 million in
cash flow
improvements
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Operational results
Average days in AR reduced by 7 days
Average % of insurance AR over 90 days reduced to 8%
Timely filing write-offs as compared to net revenue down from
.9% to .4%
Number of accounts needing follow-up per FTE down from 719
to 339
Current staff is gaining ground on backlog and is measurably
more satisfied
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Financial results
$20.6 million in accelerated cash flow
$1.1 million net impact in timely filing improvement
$260,000 in FTE annual savings
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What’s next for Avera
Health with RPA?
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Questions?
Mary Wickersham
VP, Central Business Office
mary.wickersham@averahealth.org
Ryan Ayres
SVP, Strategic Solutions
ryan.ayres@recondotech.com